README.md

metadata

language:
  - en
base_model: google-t5/t5-base
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: MRPC
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8970588235294118
          - name: F1
            type: f1
            value: 0.926829268292683

MRPC

This model is a fine-tuned version of google-t5/t5-base on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

• Loss: 0.5629
• Accuracy: 0.8971
• F1: 0.9268
• Combined Score: 0.9119

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Accuracy	Combined Score	F1	Validation Loss
No log	1.0	115	0.7108	0.7671	0.8234	0.5476
No log	2.0	230	0.8701	0.8901	0.9100	0.3523
No log	3.0	345	0.8725	0.8924	0.9122	0.3624
No log	4.0	460	0.8775	0.8949	0.9123	0.3646
0.3744	5.0	575	0.8946	0.9099	0.9252	0.4054
0.3744	6.0	690	0.8897	0.9057	0.9217	0.4624
0.3744	7.0	805	0.5530	0.8873	0.9212	0.9042
0.3744	8.0	920	0.5405	0.8897	0.9220	0.9059
0.0877	9.0	1035	0.5629	0.8971	0.9268	0.9119
0.0877	10.0	1150	0.5856	0.8922	0.9241	0.9081

Framework versions

• Transformers 4.43.3
• Pytorch 1.11.0+cu113
• Datasets 2.20.0
• Tokenizers 0.19.1